Models and exact methods for assembly line balancing problems with assignment restrictions

Abstract

Manufacturing lines made possible the large-scale production of complex products. Considering the significant implementation costs, designing and operating manufacturing lines economically is imperative to guarantee high productivity. Therefore, reaching a workload equilibrium for the different assembly line (work)stations is essential. In other words, there is a need to propose solutions for the Assembly Line Balancing Problem (ALBP). Although predominantly conceptual, the Simple Assembly Line Balancing Problem (SALBP) is the benchmark for the line balancing subject. Such an approach results in efficient solutions that satisfy demand requirements and optimize operating costs. However, the design and operation of lines often require meeting the satisfaction of real-world constraints not considered in SALBP. This work proposes and discusses three studies involving model and exact methods for assembly line balancing problems with assignment restrictions, bringing different contributions to the theme. Lexicographical approaches are adopted for the solution methods, and mathematical models are implemented in solvers to conduct computational optimization experiments. The first work deals with ergonomic constraints for manually operated SALBPs (ErgoSALBP). A Mixed-Integer Linear Programming (MILP) is formulated with the main objective of minimizing the number of stations for a given cycle time and reducing the total costs at the desired production rate. The secondary objective is to meet the ergonomic requirements to prevent musculoskeletal disorders in workers. An analysis is also performed to determine the level of ergonomic risks among assembly line workers. The second work contemplates the Multi-manned Assembly Line Balancing Problem (MALBP). This type of line is typical for large-size products and allows several workers to be allocated to the same station só that different tasks may be processed simultaneously on the same product. An exact procedure using MILP and Constraint Programming (CP) methods is proposed to solve challenging instances, outperforming previously proposed methods regarding solution quality. The main objective is to minimize the number of workers in the assembly line, and the secondary objective is to minimize the number of stations. The third work extends the second one by considering Assignment Restrictions (Ars) related to transformed resources. Several scenarios found in real-world assembly lines are implemented to propose the most complete model in the literature for the Assignment Restricted Assembly Line Balancing Problem (ARALBP). Lastly, the contributions from the developed papers are described, and future research opportunities are presented.